tigeR
tigeR is an R package designed for the analysis of gene expression in tumor immunotherapy.
1.Introduction
1060 samples with immunotherapy clinical information from 11 melanoma datasets, including 3 lung cancer datasets, 2 kidney cancer datasets, 1 gastric cancer dataset, 1 low-grade glioma dataset, 1 glioblastoma dataset and 1 Head and Neck Squamous data set (all organized into R language ‘SummarizedExperiment’ objects).
23 immunotherapy response related biomarkers from literature, multiple methods for analysis and visualization.
10 open source tumor microenvironment deconvolution methods including CIBERSORT, TIMER, ESTIMATE, IPS, xCell, EPIC, ConsensusTME, ABIS, quanTIseq, and MCPCounter. Several downstream method for analysis and visualization.
6 machine learning method for multi-modal prediction model construction and testing.
Overall design of tigeR
2.Installation
packages <- c("BiocManager", "devtools", "ggplot2", "pROC")
for (package in packages) {
if (!require(package, character.only = TRUE)) {
install.packages(package)
}
}
devtools::install_github("YuLab-SMU/tigeR")3.Quick Start
The workflow of tigeR is below, see more details in tigeR documentation.
Workflow of tigeR